Laboratory Automation Tools and Throughput Gains in Materials Discovery Projects: Survey Experiment

Authors

  • Seung-Ho Jung Department of Communication, College of Social Sciences, Gyeongsang National University, Jinju-si, Gyeongsangnam-do, Republic of Korea Author
  • Bo-Ram Seok Department of Communication, College of Social Sciences, Gyeongsang National University, Jinju-si, Gyeongsangnam-do, Republic of Korea Author

Keywords:

Materials Informatics, Laboratory Automation, Survey Experiment, Throughput Optimization, Throughput Gains

Abstract

Laboratory automation has emerged as a key paradigm for accelerating materials discovery, yet empirical quantification of its impact on research throughput remains scarce. This study presents systematic empirical evidence on how laboratory automation tools link to throughput gains in materials discovery projects. Using a randomized survey experiment with a diverse sample of materials science researchers, we evaluate the perceived and projected productivity dividends of different automation modalities, ranging from automated liquid handling to fully autonomous closed-loop synthesis systems. The empirical findings indicate that semi-automation and full automation yield highly substantial increases in project throughput compared to traditional manual workflows. However, these gains are heavily moderated by the complexity of the materials systems under study and the administrative burdens associated with programming and maintaining the robotic systems. We find that while throughput increases, the cognitive workload shifts from physical execution to software troubleshooting and data processing. These results provide critical insights for academic departments, funding agencies, and industrial research laboratories attempting to optimize resource allocation and accelerate materials design.

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Published

2026-01-17

Issue

Vol. 1 No. 1 (2026)

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Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

Articles are distributed under the Creative Commons Attribution 4.0 International License (CC BY 4.0), unless otherwise stated.